D2D Users Research Articles

Learning-Based Delay-Aware Caching in Wireless D2D Caching Networks

Recently, wireless caching techniques have been studied to satisfy lower delay requirements and offload traffic from peak periods. By storing parts of the popular files at the mobile users, users can locate some of their requested files in their own caches or the caches at their neighbors. In the latter case, when a user receives files from its neighbors, device-to-device(D2D) communication is performed. D2D communication underlaid with cellular networks is also a new paradigm for the upcoming wireless systems. By allowing a pair of adjacent D2D users to communicate directly, D2D communication can achieve higher throughput, better energy efficiency and lower traffic delay. In this work, we propose an efficient learning-based caching algorithm operating together with a non-parametric estimator to minimize the average transmission delay in D2D-enabled cellular networks. It is assumed that the system does not have any prior information regarding the popularity of the files, and the non-parametric estimator is aimed at learning the intensity function of the file requests. An algorithm is devised to determine the best <file,user> pairs that provide the best delay improvement in each loop to form a caching policy with very low transmission delay and high throughput. This algorithm is also extended to address a more general scenario, in which the distributions of fading coefficients and values of system parameters potentially change over time. Via numerical results, the superiority of the proposed algorithm is verified by comparing it with a naive algorithm, in which all users simply cache their favorite files, and by comparing with a probabilistic algorithm, in which the users cache a file with a probability that is proportional to its popularity.

Resource Allocation for D2D-Enabled Communications in Vehicle Platooning

Recent studies have shown that traffic safety and efficiency can be substantially improved by vehicle platooning, in which the platoon’ stability is ensured through the exchange of control information among vehicles. So, it is a key issue to share control information efficiently and timely. Proximity-based device-to-device (D2D) communications with high transmission rate, can provide a promising solution to the above issue. In this paper, a platoon leader evaluation-based two-stage platoon formation algorithm is proposed to form stable platoons, which can significantly reduce the spectrum resource overhead and improve the safety of vehicle platooning. After that, we propose a predecessor-following communication mode-based on D2D, ensuring high-rate transmission of control information. Moreover, we propose time division-based intra-platoon and minimum rate guaranteed inter-platoon resource allocation mechanisms, which aims at allocating resources for D2D users efficiently within the platoon and optimize cellular users’ rate, respectively. Numerical results show that the proposed mechanism and algorithm can not only significantly improve spectrum resource utilization, but also guarantee the platoon stability.

A multi-armed bandit solver method for adaptive power allocation in device-to-device communication

Device to device (D2D) communication has attracted enormous attention for future cellular networks which helps to increase the cellular capacity, improve the user throughput, and extend the battery lifetime of user equipments (UEs) by reusing the spectrum resources. However, D2D devices provide interferences in the system while reusing the resources. Proper control of interferences helps to increase the performance of the overall system. Adaptive power allocation among cellular and D2D users contributes to providing an efficient interference management system. In this paper, we propose an online power allocation method, i.e., multi-armed bandit solver for D2D communication. We explore the proposed method to improve the system throughput and D2D throughput as well. We incorporate the set of states for this learning algorithm with the appropriate number of system-defined variables, which increases the observation space and consequently improve the balance of spectrum usage. Finally, we compare our proposed work with existing distributed reinforcement learning and random allocation of resources. Simulation results depict that the proposed resource allocation method outperforms the existing works regarding overall system throughput as well as D2D throughput by efficiently controlling the interference levels.

Channel Access and Power Control for Mobile Crowdsourcing in Device‐to‐Device Underlaid Cellular Networks

With the access of a myriad of smart handheld devices in cellular networks, mobile crowdsourcing becomes increasingly popular, which can leverage omnipresent mobile devices to promote the complicated crowdsourcing tasks. Device‐to‐device (D2D) communication is highly desired in mobile crowdsourcing when cellular communications are costly. The D2D cellular network is more preferable for mobile crowdsourcing than conventional cellular network. Therefore, this paper addresses the channel access and power control problem in the D2D underlaid cellular networks. We propose a novel semidistributed network‐assisted power and a channel access control scheme for D2D user equipment (DUE) pieces. It can control the interference from DUE pieces to the cellular user accurately and has low information feedback overhead. For the proposed scheme, the stochastic geometry tool is employed and analytic expressions are derived for the coverage probabilities of both the cellular link and D2D links. We analyze the impact of key system parameters on the proposed scheme. The Pareto optimal access threshold maximizing the total area spectral efficiency is obtained. Unlike the existing works, the performances of the cellular link and D2D links are both considered. Simulation results show that the proposed method can improve the total area spectral efficiency significantly compared to existing schemes.

Joint Mode Selection and Resource Allocation for Scalable Video Multicast in Hybrid Cellular and D2D Network

Scalable wireless video multicast has been widely studied as an efficient mechanism for real-time video transmission, and scalable video coding alongside adaptive modulation and coding is proposed to address the heterogeneity of networks and user capabilities in next generation mobile communication networks. This paper combines D2D technology with the traditional cellular network to form a hybrid network to improve video subscriber users' experience. The proposed scheme is formulated into a joint mode selection, resource, and power allocation problem based on interference mitigation, which is proven to be NP-hard. Then, we divide it into two sub-problems, where the first one is model selection to maximize the number of D2D users who can access the systems, and the other is to assign appropriate MCS and resource blocks to each video layer. To solve these two problems, we present a greedy algorithm and a heuristic algorithm, respectively. Simulation results show that our hybrid cellular and D2D communications network can effectively increase the capacity of system users, and the mixed network video multicast model can improve the overall system throughput while providing better video quality.

Power Allocation for Maximizing Uplink Rate Over Full-Duplex Relay-Based D2D Communication Underlying Cellular Networks

Device-to-device (D2D) communications, which can increase system throughput, allow two cellular devices to communicate directly with each other. Compared with half-duplex relay, full-duplex relay can significantly improve the spectrum efficiency if the self-interference can be efficiently eliminated. This paper proposes a D2D communication scheme, which assigns the fixed D2D transmitter as full-duplex amplify-and-forward relay to assist cellular uplink transmission. Cellular user close to the fixed D2D transmitter can directly download the video by D2D communications. An optimization problem is formulated to maximize the uplink rate of cellular user while guaranteeing the rate requirement of D2D user. We first obtain the feasible region of the power splitting factor, which characterizes the proportion of fixed D2D transmitter power allocated to cellular uplink and D2D communications. Then, a closed-form expression of the optimal power allocation scheme is derived. Also simulation results are presented to validate the proposed optimal power allocation scheme for uplink rate maximization.

Device-to-Device Communications Underlying UAV-Supported Social Networking

The integration of device-to-device (D2D) communications technology can further boost system performance for unmanned aerial vehicles supported pervasive social networking. In this paper, we maximize the sum social group utility of the social networking by power optimization, whereas the quality-of-service requirements of all D2D users and downlink users must be satisfied. In the proposed formulation, we consider the physical interference and social connections between users in the physical/social domain, respectively. However, the formulated problem is strongly NP-hard and intractable, to solve it we reveal the hidden non-convex components, and approximate the original problem with a sequence of more tractable convex problems. We propose an efficient semi-decentralized algorithm by decomposing the complex problem into several simple subproblems, which is proved to converge to the stationary solutions of the original problem. Simulation results show that our proposed method can achieve comparable performance but much less time complexity than the centralized method and obtain superior performance.

Capacity Improvement for Full Duplex Device-to-Device Communications Underlaying Cellular Networks

In this paper, the capacity improvement of full-duplex (FD) device-to-device (D2D) underlaying cellular networks (CNs) is analyzed. A single-cell environment is considered with one half-duplex (HD) base station, multiple HD cellular user equipments (CUEs), and one pair of FD D2D user equipments (DUEs). The BS is equipped with ${M}$ multiple antennas, and one pair of FD DUEs is permitted to share the same resource with ${M}$ out of ${K}$ uplink HD CUEs, which will lead to a more complex interference environment. First, a novel interference-limited area-based (ILA-based) scheme is proposed to manage the co-channel interference from CN CUEs to FD DUEs. The ILA-based scheme does not allow the coexistence of HD CUEs and FD DUEs if the HD CUEs are located in any region of the two ILAs. Next, a senior ILA-based (SILA-based) scheme is proposed to reduce the complexity of the ILA-based scheme, in which only a common ILA is designed for both FD DUEs instead of the two ILAs in the ILA-based scheme. Then, the lower bounds of the ergodic capacity for FD D2D communications with imperfect self-interference cancellation (SIC) are derived in closed-forms with the ILA-based scheme and the SILA-based scheme. Furthermore, the capacity gain of the FD D2D communications is analyzed, and the numerical results show that the capacity improvement of the FD D2D communications is much greater than the traditional HD D2D communication if the sufficient SIC is achieved.

Device-centric resource allocation scheme for 5G networks

Device-centric architecture is an important aspect for fifth generation (5G) networks. The current cellular systems are base station-centric where the base-station (BS) is responsible for resource allocation. The BS allocates resources to users based on their channel state information (CSI) and feedback. This resource allocation process increases load at the BS side resulting in more time consumption. This decreases the overall network throughput and increases delay in resource allocation. Therefore, in this article, a device-centric resource allocation scheme is proposed for D2D users. In this scheme, interested D2D pairs can allocate the resource to themselves using the following three steps. In first step, devices maintain their resource occupancy matrix by exchanging the neighbouring information. In second step, a resource block is selected based on resource allocation scenarios. In third steps, resource block is allocated based on the priority on the BS side. The proposed scheme is less dependent on the BS side, hence it reduces the load on BS side and it also reduces time consumption in resource allocation process. Additionally, the proposed scheme improves the overall network throughput. A comparison of the proposed scheme with the base-centric scheme shows that proposed scheme is up to 35% more effective in each experimental case.

Cooperative Full Duplex Device to Device Communication Underlaying Cellular Networks

Recently, device-to-device (D2D) communication and full duplex communication are both considered key technologies for 5G networks. In this paper, two novel cooperative modes are developed for full duplex D2D communication underlaying cellular networks: the network MU-MIMO based mode (N-mode) and the sequential forwarding mode (S-mode). In the N-mode, two D2D users work as network MIMO to forward the data to cellular users and thus leverage the channel diversity. In the S-mode, the spatial distribution of D2D users and cellular users is explored to improve the transmission rate. Based on these modes, two D2D users share the downlink resources with two nearby cellular users simultaneously to achieve both proximity gain and reuse gain. Moreover, these modes are well suited for edge cellular users. To optimize the performance of the two modes, optimal power allocation is conducted by considering the influence of residual self-interference at full duplex radios and the requirements of the minimum transmission rate for both cellular users and D2D users. Simulation results show that, compared with the dedicated mode, the sum rate of cooperative modes in the perfect self-interference cancellation case can achieve 32% overall improvement and about 70% improvement in the scenario with non-edge D2D users and edge cellular users. With residual self-interference at a full duplex radio, the overall performance improvement is reduced to 15%. However, the cooperative modes can still achieve 40% improvement in the scenario with non-edge D2D users and edge cellular users.

Novel Device-to-Device Discovery Scheme Based on Random Backoff in LTE-Advanced Networks

Device-to-device (D2D) discovery is a key enabler of D2D communications for the direct exchange of local area traffic between proximity users (UEs) to improve spectral efficiency. The direct D2D discovery relies on the capabilities of the D2D UEs to autonomously indicate their presence to proximity D2D UEs. Despite its potential of reducing energy and signaling burden, the direct D2D discovery has not drawn adequate attention. In this paper, we propose a direct D2D discovery scheme based on the random backoff procedure, where D2D UEs randomly choose a backoff interval and retransmit a beacon. Compared with existing schemes, the performance of the proposed scheme can be significantly enhanced in terms of the discovery probability and the discovery delay. Several useful guidelines for its design are proposed based on our analysis. Finally, numerical results provide valuable insights on the performance tradeoff inherent to the proposed D2D discovery scheme.

Effective Small Social Community Aware D2D Resource Allocation Underlaying Cellular Networks

Social-aware device-to-device (D2D) resource allocation utilizes social ties in human-formed social networks to allocate spectrum resources between D2D users and cellular users. In this letter, we consider the small size social communities formed by people with similar interests and exploit them to optimize the resource allocation of the communities. This results in an optimal graph matching problem among communities to solve the D2D resource allocation problem. Solutions are derived via bipartite graph matching and an effective small social community resource allocation algorithm corresponding to the cases of small and high D2D user loads.

Maximizing throughput gain via resource allocation in D2D communications

By reusing the cellular resources, device-to-device (D2D) communication is becoming a very promising technology that greatly enhances the spectrum utilization. To harvest the benefits that D2D communications can offer, efficient resource allocation strategy is required to guarantee the demands of quality of service (QoS) for both cellular and D2D users. This paper proposes a resource allocation scheme to alleviate the performance deterioration of the D2D communications with spectrum reuse. To maximize the overall throughput gain, the proposed scheme is designed to reduce the rate loss of cellular users and improve the rate of D2D users simultaneously in a two-step manner. Specifically, it first calculates the reuse gain for a single D2D pair and a single cellular user. Next, a maximum weight bipartite matching is further proposed to select the reuse pair to maximize the overall network throughput gain. Numerical results demonstrate that the proposed resource allocation scheme can significantly improve the network throughput performance with average user rate guaranteed.

Power control and performance analysis for full‐duplex relay‐assisted D2D communication underlaying fifth generation cellular networks

Full-duplex relay-assisted device-to-device (D2D) communication underlaying fifth generation cellular networks allow devices to exchange information directly and extend coverage via relay strategy. In this study, the authors consider such a scenario, where the D2D communications assisted by fixed-location full-duplex relays in interference existing circumstance. Different from previous works, they assume that there are two types of users, cellular users and D2D users. They investigate power control problem and coverage probability performance in the previously assumed situation. Therefore, an effective power control scheme is of great importance to suppress interference between D2D and cellular communications, which can improve the total system throughput and spectral efficiency. To describe it, they formulate a power control optimisation problem for cellular communication and propose a simple on–off power control algorithm for D2D communication. They also obtain an analytic expression for the coverage probability of the cellular link using stochastic geometry according to the proposed algorithm. Simulation results follow to show the rates of both cellular and D2D links in the various numbers of D2D transceivers.

Cooperative Game-based Cheating in Full-duplex Relaying-based D2D Communication Underlaying Heterogeneous Cellular Networks

Device-to-device (D2D) communications allow direct transmissions between two adjacent user devices, which can improve system performance in cellular networks. Considering full-duplex (FD) relaying outperforms half-duplex (HD) relaying in spectrum and energy efficiency, we apply the FD relaying-based D2D communication scheme in heterogeneous cellular network, which allows D2D links to underlay cellular downlink by assigning D2D transmitters as FD relays to assist cellular downlink transmissions. Although the scheme can improve the utilization of spectrum resource dramatically, the unreasonable resource sharing of D2D users will increase the inter-user interference. Therefore, in this paper, we try to optimize the throughput of D2D users on the premise of ensuring the quality of service (QoS) of cellular users. To this end, we first propose a D2D transmit power-allocation scheme and use Gale-Sharpley (GS) algorithm in matching theory to solve the resource allocation problem. Next, a Cheating algorithm based on cooperative game theory is proposed to further improve the throughput of D2D users. More importantly, due to the NP-hardness of finding the optimal solution of Cheating algorithm, we propose a heuristic algorithm based on depth first search (DFS) which using different colors to represent the different statements of D2D users to find a near-optimal solution. The simulation results show that the proposed algorithm compared with GS algorithm can significantly improve the total throughput of D2D users, and it also has lower complexity and better throughput performance against existing Cheating algorithm.

Discrete location‐aware resource allocation for underlay device‐to‐device communications in cellular networks

Device-to-device (D2D) communications underlaying a cellular network is an efficient way to enhance spectral efficiency via resource sharing between D2D and cellular users (CUs). In this study, a discrete location-aware (DLA) interference model for D2D users is presented to allocate cellular resources. The vicinity of a CU is discretised into multiple regions, and the number of active D2D users in each region is constrained to satisfy the CU QoS requirements. Considering the locations of D2D users affecting the interference to CUs and thus the achievable rate, the formulated non-linear 0–1 knapsack resource allocation (RA) problem is divided into two subproblems: (i) the optimal amount of shared resources between the two types of users; (ii) the optimum subset of D2D users which transmit. The conditions of D2D users spatial deployment and resources reuse portion to achieve the solutions of the two subproblems are theoretically derived and proven. Then a DLA-RA algorithm is proposed to solve the corresponding subproblems in both single CU and multiple CUs cases. Extensive simulations results are presented which verify the effectiveness of the proposed DLA interference model and the RA scheme.

Efficient Resource Allocation in Device-to-Device Communication Using Cognitive Radio Technology

Device-to-device (D2D) communication is developed as a new paradigm to enhance network performance according to LTE and WiMAX advanced standards. The D2D communication may have dedicated spectrum (overlay) or shared spectrum (underlay). However, the allocated dedicated spectrum may not be effectively used in the overlay mode, while interference between the D2D users and cellular users cause impairments in the underlay mode. Can the resource allocation of a D2D system be optimized using the cognitive approach where the D2D users opportunistically access the underutilized radio spectrum? That is the focus of this paper. In this paper, the transmission rate of the D2D users is optimized while simultaneously satisfying five sets of constraints related to power, interference, and data rate, modeling D2D users as cognitive secondary users. Furthermore, a two-stage approach is considered to allocate the radio resources efficiently. A new adaptive subcarrier allocation scheme is designed first, and then, a novel power allocation scheme is developed utilizing geometric water-filling approach that provides optimal solution with low computation complexity for this nonlinear problem. Numerical results show that the proposed approach achieved significant performance enhancement than the existing schemes.

Throughput-Aware Cooperative Reinforcement Learning for Adaptive Resource Allocation in Device-to-Device Communication

Device-to-device (D2D) communication is an essential feature for the future cellular networks as it increases spectrum efficiency by reusing resources between cellular and D2D users. However, the performance of the overall system can degrade if there is no proper control over interferences produced by the D2D users. Efficient resource allocation among D2D User equipments (UE) in a cellular network is desirable since it helps to provide a suitable interference management system. In this paper, we propose a cooperative reinforcement learning algorithm for adaptive resource allocation, which contributes to improving system throughput. In order to avoid selfish devices, which try to increase the throughput independently, we consider cooperation between devices as promising approach to significantly improve the overall system throughput. We impose cooperation by sharing the value function/learned policies between devices and incorporating a neighboring factor. We incorporate the set of states with the appropriate number of system-defined variables, which increases the observation space and consequently improves the accuracy of the learning algorithm. Finally, we compare our work with existing distributed reinforcement learning and random allocation of resources. Simulation results show that the proposed resource allocation algorithm outperforms both existing methods while varying the number of D2D users and transmission power in terms of overall system throughput, as well as D2D throughput by proper Resource block (RB)-power level combination with fairness measure and improving the Quality of service (QoS) by efficient controlling of the interference level.

Joint Beamforming and Resource Allocation for Wireless-Powered Device-to-Device Communications in Cellular Networks

In this paper, we develop wireless-powered device-to-device (D2D) communications underlaying a time-division duplex cellular network, where D2D users (DUs) coexist with cellular users (CUs) and harvest energy from a base station during the downlink time for sustaining communications during the uplink time. Two spectrum access modes, coexistence and hybrid, are considered for the DUs. Our goal is to maximize the sum rate of the DUs by jointly designing beamforming and time allocation as well as DU transmit power, while maintaining the quality-of-service for the CUs. In a single DU scenario, the joint design problems in the downlink and uplink are decoupled and solved in sequence. By doing so, the optimal downlink beamforming is found via a semi-definite relaxation (SDR) approach. From a DU power control perspective, a scheme is proposed for obtaining the optimal solution of the remaining uplink design in the coexistence and hybrid modes. For a scenario with multiple DUs, a converted SDR problem is considered to attain the optimal solution of the original problem when the uplink receive beamforming is appropriately predetermined to null out the DU interference. We present simulation results to quantify the impact of various network parameters on the performance of the proposed schemes.

Energy Efficiency and Spectrum Efficiency Tradeoff in the D2D-Enabled HetNet

We investigate the tradeoff between energy efficiency (EE) and spectrum efficiency (SE) in the heterogeneous network composed of a macro base station (BS), several pico BSs, and device-to-device (D2D) communication pairs during the uplink transmission. A utility function of the tradeoff between EE and SE is defined first. Then, we formulate the tradeoff utility maximization problem as a joint channel allocation and power control problem for cellular and D2D users. The original problem is transformed into a more tractable subtractive form, and we further decompose the problem into several subproblems that can be solved separately. Numerical results confirm the effectiveness of the proposed scheme and offer valuable insights. Compared with EE, SE is much less sensitive to the variation of the tradeoff factor, which indicates that our proposed scheme can achieve high EE while guaranteeing a fairly large value of SE with a properly chosen EE–SE tradeoff factor.